PPT-CSE 486/586 Distributed Systems

Byzantine Fault Tolerance 1 Steve Ko Computer Sciences and Engineering University at Buffalo Recap Digital certificates Binds a public key to its owner Establishes a chain of trust TLS. Concurrency Control --- 3. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Strict execution of transactions?. Delay . both their read and write operations . on an . object until . Paxos. --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Paxos. is a consensus algorithm.. It allows multiple acceptors accepting multiple proposals.. A proposer always makes sure that,. Paxos. --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Paxos. is a consensus algorithm.. It allows multiple acceptors.. It allows multiple proposals to be accepted.. Case Study: Amazon Dynamo. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. CAP Theorem?. Consistency, Availability, Partition Tolerance. Pick two. Eventual consistency?. Availability and partition tolerance over consistency. New Trends in Distributed Storage. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Two important components in a distributed file service?. Directory service. Flat file service. Leader . Election --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Algorithm 2: Modified Ring Election . election . message tracks . all. IDs of nodes that forwarded it, not just the highest. Concurrency . Control --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap: Transactions. Transactions?. Abstraction for . grouping multiple operations into one. Transaction primitives?. Gossiping. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Consistency models. Linearizability. Sequential consistency. Causal consistency. Eventual consistency. Depending on application scenarios, one consistency model makes more sense that others.. Byzantine Fault Tolerance --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Spanner. Geo-distributed database. Supports a relational data model with a SQL-like language. Google Spanner. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Digital certificates. Binds a public key to its owner. Establishes a chain of trust. TLS. Provides an application-transparent way of secure communication. Paxos. --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. NFS. Caching with write-through policy at close(). Stateless server. One power efficient design: FAWN. Embedded CPUs & Flash . Gossiping. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Available copies replication?. Read and write . p. roceed with live replicas. Cannot achieve one-copy serialization itself. Case Study: Facebook f4. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Engineering principle. Make the common case fast, and rare cases correct. Power law. Haystack. A design for warm photos. Global States. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Last Time. Ordering of events. Many applications need it, e.g., collaborative editing, distributed storage, etc.. Logical time.